组织信息化环境下知识流动对组织创造力的影响

通过解析知识流动和组织信息化环境的内部构成，探究知识溢出/知识扩散、高管支持/ICT应用对组织创造力的差异性影响，以及不同组织信息化环境对知识流动与组织创造力关系的调节作用。利用信息化程度较高的企业数据，使用层级回归分析进行实证检验。结果表明：组织创造力受知识流动的正向影响，知识扩散对其的正向影响更强；组织信息化正向影响组织创造力，相比ICT应用，高管支持对组织创造力的正向影响更强；高管支持在知识溢出/知识扩散与组织创造力之间的正向调节作用显著；ICT应用对知识扩散与组织创造力的强化作用显著强于对知识溢出与组织创造力之间的调节作用。     

Do special issues offer something special? An overview of research trends in Telecommunications Policy special issues

This study explores the value of special issues by analyzing the characteristics of special issues of Telecommunications Policy (TP). Specifically, this study examines the status of special issue publications, the characteristics of their articles compared with those of general issues, and the factors affecting article citations. For the analysis, all information on TP articles published from 1976 to 2018 was collected from the Scopus database. A comparative analysis as well as a negative binomial regression were conducted on papers published after 1994, when the first special issue was published. The results show that special issues are distinguished from general issues by various characteristics, such as multinational author collaboration, number of references, keywords, and funding. While general issue papers are more frequently cited in academia, special issue papers show better performance in terms of online captures and social media sharing. Moreover, the smaller number of variables affects the frequency of citations in the case of special issues, revealing that content and format are more influential than author factors.     

Monetary policy and food inflation in South Africa: A quantile regression analysis

Although optimal monetary policy stabilizes food inflation theoretically, empirical studies remain limited not only in the context of volumes and the estimation approaches, but are focused on selected advanced and emerging countries to the neglect of Africa where poverty and dominance of food in the consumption basket are more pronounced. We provide empirical evidence in the context of South Africa using quantile regressions. Rising food prices are destabilized even further by restrictive monetary policy; a finding that has ramifications for inflation targeting, especially given that a quarter of the country’s population is food poor.     

债务违约、社会责任与政府支持

转型期中国，地方国有企业作为地区经济发展的一股中坚力量，当其发生债务违约时，作为实际控制人的地方政府究竟是否愿意提供支持，会优先选择哪些企业提供支持，政府的支持行为是否会影响到信贷资源的配置效率呢?为得到验证，文章选取2007-2016年沪深A股地方国有上市企业作为研究样本，实证分析了地方国企发生债务违约后，地方政府的支持行为及其对信贷资源配置效率的影响。研究结论表明：第一，地方国企发生债务违约后，地方政府会提供更多的"支持"，且支持额度与债务违约额呈显著正相关关系；第二，债务违约前，承担了更多社会责任（环保投资、捐赠以及就业等）的地方国企，在债务违约后可相应地获得更多的地方政府支持；第三，违约企业，尤其是得到更多政府支持的违约企业可获得更多的信贷资源，而其经营业绩却往往更差。由此表明政府干预一定程度上降低了信贷资源配置效率。     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Reconciling Alternative Theories for the Safety of Owner–Operators

Motor carrier safety is an important concern of shippers, carriers, policy makers, consignees, insurance providers, and the motoring public. One aspect of carrier safety that has garnered substantial attention is whether carriers making greater use of owner–operators are more or less safe vis‐à‐vis carriers making greater use of employee drivers. Currently, conflicting theoretical predictions exist regarding the direction of this relationship. In this article, we offer a reconciliation of the alternative theoretical predictions by developing a coherent theory that merges sociological rational choice theory and theory regarding motor carrier safety. We subject our theory to empirical testing by fitting a series of seemingly unrelated regression models to a vector of safety measures tracked as part of the Federal Motor Carrier Safety Administration's Compliance, Safety, and Accountability program. Our results are consistent with our proposed theory of owner—operator safety and provide meaningful theoretical and managerial implications and directions for future research.     

Labor market analysis through transformations and robust multivariate models

The work presents a robust approach to labor share analysis. The estimate of labor share presents various complexities related to the nature of the data sets to be analyzed. Typically, labor share is evaluated by using discriminant analysis and linear or generalized linear models, that do not take into account the presence of possible outliers. Moreover, the variables to be considered are often characterized by a high dimensional structure. The proposed approach has the objective of improving the estimation of the model using robust multivariate regression techniques and data transformation.     

数据仓库相关问题的探讨

综述了数据仓库的概念、特点、结构及其关键技术，对创建数据仓库系统过程中存在的有关问题进行了探讨，并展望了其发展趋势。